Biomedical and Health Sciences
This is the supplementary material for the paper "A multimodal AI system for out-of-distribution generalization of seizure identification" in IEEE Journal of Biomedical and Health Informatics.
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A global increase in the prevalence of obesity and type 2 diabetes is strongly connected to an increased prevalence of non-alcoholic fatty liver disease (NAFLD) worldwide. In this article, the progression of the NAFLD process is modeled by continuous time Markov chains (CTMCs) with nine states. Maximum likelihood is used to estimate the transition intensities among the states. Once the transition intensities are obtained, the mean sojourn time and its variance are estimated, and the state probability distribution and its asymptotic covariance matrix are also estimated.
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I tackle the problem of non-alcoholic fatty liver disease (NAFLD) from the statistical point of view. Using the multistate model, in the form of the continuous time Markov chains, helps the statistical analysis of the progression of the disease over time. The simplest model of the health-disease-death process is applied to the NAFLD. The model is composed of 8 pdfs and 5 rates that need to be estimated. Maximum likelihood and quasi-Newton methods are applied to estimate the transition rates among states.
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Asthma is a common, usually long-term respiratory disease with negative impact on society and the economy worldwide. Treatment involves using medical devices (inhalers) that distribute medicationto the airways, and its efficiency depends on the precision of the inhalation technique. Health monitoring systems equipped with sensors and embedded with sound signal detection enable the recognition of drug actuation and could be powerful tools for reliable audio content analysis.
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This dataset was prepared to aid in the creation of a machine learning algorithm that would classify the white blood cells in thin blood smears of juvenile Visayan warty pigs. The creation of this dataset was deemed imperative because of the limited availability of blood smear images collected from the critically endangered species on the internet. The dataset contains 3,457 images of various types of white blood cells (JPEG) with accompanying cell type labels (XLSX).
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EEG consists of collecting information from brain activity in the form of electrical voltage. Epileptic Seizure prediction and detection is a major sought after research nowadays. This dataset contains data from 11 patients of whom seizures are observed in EEG for 2 patients.
The total duration of seizures is 170 seconds. The number of channels is 16 and data is collected at 256Hz sampling rate.
The final dataset files in .csv format contain 87040 rows x 17 columns,
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one hundred fifty patients were followed up every year for 28 years, and at each visit the characteristics of the patients were recoreded ( these are the predictors) like: sex( 0= female, 1= male) , age, BMI, LDL-chol, HOMA2-IR, systolic blood pressure and diastolic blood pressure. For each partipant, the recorded value is the mean of the follow up measurements. The age is the median value. The response variables are the transition counts among the states of the process of the disease ( fibrosis in NAFLD ) evolving over time .
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This is the augmentation dataset used in the paper named "LSTformer: Long Short-term Transformer for Real Time Respiratory
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Screening tools play a vital role in sensory processing disorder detection. The automatic collection of features related to behavioral parameters and the response to given stimuli is possible with the recent technology. Real time stress related health parameters are collected as response to visual stimuli created with experts’ suggestions based on visual sensory processing related questionnaire. Body temperature and heart rate are obtained by smart watch.
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Today, Mental health problems are getting grave and need technological solutions. Irrational anticipated fear is Anxiety Disorder. Specific Phobia disorders are a type of Anxiety disorder; these phobias are rarely detected in clinical settings and are presence indicators of other serious mental problems. VR is considered a potent tool for treatment and diagnosis.
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